image

How Many Innovations Need to Be Produced in the Process of Endogenous Growth with Fluid Intelligence

Download Paper PDF: Download pdf
Author(s):
Abstract:

In innovation-based endogenous (Schumpeterian) growth theory, the production of innovations is constrained basically by the finite nature of the labor supply. In this paper, I show that innovations are constrained because (1) the amount of fluid intelligence of researchers in an economy is limited and (2) the returns on investments in technologies and in capital are kept equal through arbitrage in markets. With these constraints, equilibrium values of the number of researchers and their average productivity in an economy exist, and the equilibrium value of average productivity determines the amount of innovation production in each period. Distributions of fluid intelligence among researchers are most likely heterogeneous across economies, but if economies are open to each other, an economy with a smaller number of researchers with a high level of fluid intelligence can grow at the same rate as an economy with more of them.


© 2022 The Author(s). This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited.


How to cite:

Harashima, T. (2022). How Many Innovations Need to Be Produced in the Process of Endogenous Growth with Fluid Intelligence. Journal of Applied Economic Sciences, Volume XVII, Summer, 2(76): 107 – 121. https://doi.org/10.57017/jaes.v17.2(76).03

References:

[1] Philippe, A. and Peter Howitt, P. 1992. A Model of Growth through Creative Destruction, Econometrica, Volume 60, pp. 323–351. DOI: https://doi.org/10.2307/2951599

[2] Philippe, A. and Peter Howitt, P. 1998. Endogenous Growth Theory, Cambridge, MA, MIT Press.

[3] Philippe, A., Akcigit, U. and Peter Howitt, P. 2014. What Do We Learn from Schumpeterian Growth Theory? in: Philippe Aghion and Steven Durlauf (ed.), Handbook of Economic Growth, Volume 2, pp. 515-563.

[4] Cattell, R.B.1963. Theory of Fluid and Crystallized Intelligence: A Critical Experiment, Journal of Educational Psychology, Volume 54, pp. 1-22. DOI: https://doi.org/10.1037/h0046743

[5] Cattell, R.B. 1971. Abilities: Their Structure, Growth, and Action, Houghton Mifflin, Boston.

[6] Dinopoulos, E. and Thompson, P. 1998. Schumpeterian Growth without Scale Effects, Journal of Economic Growth, Volume 3, pp. 313–335.

[7] Eicher, T.S. and Turnovsky, S.J. 1999. Non-Scale Models of Economic Growth, The Economic Journal, Volume 109, pp. 394–415. DOI: https://doi.org/10.1111/1468-0297.00454

[8] Grossman, G.M. and Helpman, E. 1991. Innovation and Growth in the Global Economy, Cambridge, MA, MIT Press.

[13] Harashima, T. 2016. A Theory of Total Factor Productivity and the Convergence Hypothesis: Workers’ Innovations as an Essential Element, Journal of Kanazawa Seiryo University, 50(1): 55-80, in Japanese.

[14] Harashima, T. 2017. Sustainable Heterogeneity: Inequality, Growth, and Social Welfare in a Heterogeneous Population, Journal of Kanazawa Seiryo University, 51(1): 31-80, in Japanese.

[16] Harashima, T. 2018b. Wage Inequality and Innovative Intelligence-Biased Technological Change, Theoretical and Practical Research in Economic Fields, Volume IX, Summer, 1(17): 17-24.

[17] Harashima, T. 2019a. Do Households Actually Generate Rational Expectations? “Invisible Hand” for Steady State, Journal of Kanazawa Seiryo University, 52(2): 49-70, in Japanese.

[18] Harashima, T. 2019b. An Asymptotically Non-Scale Endogenous Growth Model, Journal of Kanazawa Seiryo University, 52(2): 71-86, in Japanese.

[19] Harashima, T. 2020a. A Theory of Intelligence and Total Factor Productivity: Value Added Reflects the Fruits of Fluid Intelligence, Journal of Kanazawa Seiryo University, 53(2): 65-82, in Japanese.

[20] Harashima, T. 2020b. Why Is Risk Aversion Essentially Important for Endogenous Economic Growth? Journal of Applied Economic Sciences, Volume XV, 3(69): 556-569. 

[21] Harashima, T. 2020c. The Correlation between Time Preference and Incomes Is Spurious: They Are Bridged by Fluid Intelligence, Journal of Applied Economic Sciences, Volume XV, Spring, 1(67): 107-123.

[22] Jones, Charles I. 1995a. Time Series Tests of Endogenous Growth Models, Quarterly Journal of Economics, 110(2): 495–525. DOI: https://doi.org/10.2307/2118448

[23] Jones, C.I. 1995b. R&D-Based Models of Economic Growth, Journal of Political Economy, 103(4): 759–84. DOI: https://doi.org/10.1086/262002

[24] Jones, C.I. 1999. Growth: With or without Scale Effects? The American Economic Review, 89(2): 139-144. DOI: 10.1257/aer.89.2.139

[25] Kortum, S.S. 1997. Research, Patenting, and Technological Change, Econometrica, 65: 1389–1419. DOI: https://doi.org/10.2307/2171741

[26] Lord, F.M. and Novick, M.R. 1968 Statistical Theories of Mental Test Scores, Addison-Wesley, Reading, MA. 

[27] Peretto, P. 1998. Technological Change and Population Growth, Journal of Economic Growth, 3: 283–311. DOI:10.1023/A:1009799405456

[28] Peretto, P. and Smulders, S. 2002. Technological Distance, Growth and Scale Effects, The Economic Journal, 112: 603–624. DOI: https://doi.org/10.1111/1468-0297.00732

[29] Romer, P. M. 1990. Endogenous Technological Change, Journal of Political Economy, 98(5): 71–102. 

[30] Segerstrom, P. 1998. Endogenous Growth without Scale Effects, American Economic Review, 88: 1290–1310.

[31] Young, A. 1998. Growth without Scale Effects, Journal of Political Economy, Volume 106: 41–63. DOI: https://doi.org/10.1086/250002

[32] van der Linden, Wim J. and Hambleton, R.K. (Eds.). 1997. Handbook of Modern Item Response Theory, Springer-Verlag, New York.